The growing global energy demand and the need to mitigate greenhouse gas emissions have driven the explo-ration of sustainable and efficient energy solutions.In Algeria,where the energy sector relies heavily on fossil...The growing global energy demand and the need to mitigate greenhouse gas emissions have driven the explo-ration of sustainable and efficient energy solutions.In Algeria,where the energy sector relies heavily on fossil fuels,integrating renewable energy systems is essential for enhancing energy security and reducing environ-mental impacts.This study focuses on optimizing a hybrid renewable energy system(HRES)for off-grid appli-cations in the Hassi Messaoud region of Algeria to balance technical performance,economic viability,and environmental sustainability.A hybrid system consisting of photovoltaic(PV)panels,wind turbines(WTs),fuel cells(FCs),and diesel generators(DGs)was modeled and optimized using a genetic algorithm(GA).The opti-mization process aims to minimize the annual cost of the system while ensuring high reliability,as measured by the loss of power supply probability,and maximizing the use of renewable energy.A particle swarm optimization(PSO)approach was also implemented for comparison,highlighting the advantages of the GA in terms of cost distribution and system reliability.The optimized HRES demonstrated that renewable sources(PV and WT)provided 77%of the total energy demand,with an overall system cost of 0.18080$⋅kWh^(-1),significantly lower than recent studies,which reported costs between 0.213 and 0.609$⋅kWh^(-1).FCs contributed 14%to the load,whereas DGs were limited to 8%to minimize emissions,resulting in annual CO_(2) emissions of 10,865 kg and a relative emission rate of 3.608 gCO_(2)eq⋅kWh^(-1).Economic analysis showed that DGs and FCs accounted for 44%and 24%of the annual cost,respectively,highlighting the impact of backup systems in ensuring reliability.Sensitivity analysis under varying load demands and renewable energy availability confirmed the robustness of the system,and the GA approach was found to be more effective than PSO in maintaining cost efficiency and reliability.Additionally,the social analysis highlighted a renewable fraction of 91.5%,emphasizing the contribution of the system to sustainable energy practices.These findings validate GA-based optimization as a superior method for designing cost-effective,reliable,and environmentally sustainable HRES,offering significant potential to reduce fossil fuel dependency in industrial applications.These results not only support the broader adoption of renewable energy systems in similar regions but also contribute valuable insights for future research and policy development in the field of energy sustainability.展开更多
Large renewable penetration has been witnessed in power systems, resulting in reduced level of system inertia and increasing requirements for frequency response services. There have been plenty of studies developing f...Large renewable penetration has been witnessed in power systems, resulting in reduced level of system inertia and increasing requirements for frequency response services. There have been plenty of studies developing frequency-constrained operation models for power system security. However, most existing literature only focuses on operational level rather than planning level. To fill this gap, this paper proposes a novel planning model for the optimal sizing problem of integrated power and gas systems, capturing both under and over frequency security requirements. A detailed unit commitment setup considering different ramping rates is incorporated into the planning model to accurately represent the scheduling behavior of each individual generator and accurate inertia calculation. The power importing and exporting behaviors of interconnectors are considered, which can influence the largest loss of generation and demand, accounting for under and over frequency security, respectively. Additionally, a deep learning-based clustering method featured by concurrent and integrated learning is introduced in the planning model to effectively generate representative days. Case studies have been conducted on a coupled 6-bus power and 7-node gas system as well as a 14-bus power and 14-node gas system to verify the effectiveness of the proposed planning model in accurate clustering performance and realistic investment decision making.展开更多
Power loss and voltage uncertainty are the major issues prevalently faced in the design of distribution systems.But such issues can be resolved through effective usage of networking reconfiguration that has a combinat...Power loss and voltage uncertainty are the major issues prevalently faced in the design of distribution systems.But such issues can be resolved through effective usage of networking reconfiguration that has a combination of Distributed Generation(DG)units from distribution networks.In this point of view,optimal placement and sizing of DGs are effective ways to boost the performance of power systems.The optimum allocation of DGs resolves various problems namely,power loss,voltage profile improvement,enhanced reliability,system stability,and performance.Several research works have been conducted to address the distribution system problems in terms of power loss,energy loss,voltage profile,and voltage stability depending upon optimal DG distribution.With this motivation,the current study designs a Chaotic Artificial Flora Optimization based on Optimal Placement and Sizing of DGs(CAFO-OPSDG)to enhance the voltage profiles and mitigate the power loss.Besides,the CAFO algorithm is derived from the incorporation of chaos theory concept into conventional artificial flora optimization AFO algorithm with an aim to enhance the global optimization abilities.The fitness function of CAFO-OPSDG algorithm involves voltage regulation,power loss minimization,and penalty cost.To consider the actual power system scenario,the penalty factor acts as an important element not only to minimize the total power loss but to increase the voltage profiles as well.The experimental validation of the CAFO-OPSDG algorithm was conducted against IEEE 33 Bus system and IEEE 69 Bus system.The outcomes were examined under various test scenarios.The results of the experiment established that the presented CAFO-OPSDG model is effective in terms of reducing the power loss and voltage deviation and boost-up the voltage profile for the specified system.展开更多
An effective optimization method for the shape/sizing design of composite wing structures is presented with satisfying weight-cutting results. After decoupling, a kind of two-layer cycled optimization strategy suitabl...An effective optimization method for the shape/sizing design of composite wing structures is presented with satisfying weight-cutting results. After decoupling, a kind of two-layer cycled optimization strategy suitable for these integrated shape/sizing optimization is obtained. The uniform design method is used to provide sample points, and approximation models for shape design variables. And the results of sizing optimization are construct- ed with the quadratic response surface method （QRSM）. The complex method based on QRSM is used to opti- mize the shape design variables and the criteria method is adopted to optimize the sizing design variables. Compared with the conventional method, the proposed algorithm is more effective and feasible for solving complex composite optimization problems and has good efficiency in weight cutting.展开更多
The sap flow method is widely used to estimate forest transpiration.However,at the individual tree level it has spatiotemporal variations due to the impacts of environmental conditions and spatial relationships among ...The sap flow method is widely used to estimate forest transpiration.However,at the individual tree level it has spatiotemporal variations due to the impacts of environmental conditions and spatial relationships among trees.Therefore,an in-depth understanding of the coupling effects of these factors is important for designing sap flow measurement methods and performing accurate assessments of stand scale transpiration.This study is based on observations of sap flux density(SF_(d))of nine sample trees with different Hegyi’s competition indices(HCIs),soil moisture,and meteorological conditions in a pure plantation of Larix gmelinii var.principis-rupprechtii during the 2021 growing season(May to September).A multifactorial model of sap flow was developed and possible errors in the stand scale sap flow estimates associated with sample sizes were determined using model-based predictions of sap flow.Temporal variations are controlled by vapour pressure deficit(VPD),solar radiation(R),and soil moisture,and these relationships can be described by polynomial or saturated exponential functions.Spatial(individual)differences were influenced by the HCI,as shown by the decaying power function.A simple SF_(d)model at the individual tree level was developed to describe the synergistic influences of VPD,R,soil moisture,and HCI.The coefficient of variations(CV)of the sap flow estimates gradually stabilized when the sample size was>10;at least six sample trees were needed if the CV was within 10%.This study improves understanding of the mechanisms of spatiotemporal variations in sap flow at the individual tree level and provides a new methodology for determining the optimal sample size for sap flow measurements.展开更多
Fracture conductivity is a key factor to determine the fracturing effect.Optimizing proppant particle size distribution is critical for ensuring efficient proppant placement within fractures.To address challenges asso...Fracture conductivity is a key factor to determine the fracturing effect.Optimizing proppant particle size distribution is critical for ensuring efficient proppant placement within fractures.To address challenges associated with the low-permeability reservoirs in the Lufeng Oilfield of the South China Sea—including high heterogeneity,complex lithology,and suboptimal fracturing outcomes—JRC(Joint Roughness Coefficient)was employed to quantitatively characterize the lithological properties of the target formation.A CFD-DEM(Computational Fluid Dynamics-Discrete Element Method)two-way coupling approach was then utilized to construct a fracture channel model that simulates proppant transport dynamics.Theproppant particle size under different lithology was optimized.Theresults show that:(1)In rough fractures,proppant particles exhibit more chaotic migration behavior compared to their movement on smooth surfaces,thereby increasing the risk of fracture plugging;(2)Within the same particle size range,for proppants with mesh sizes of 40/70 or 20/40,fracture conductivity decreases as roughness increases.In contrast,for 30/50 mesh proppants,conductivity initially increases and then decreases with rising roughness;(3)Under identical roughness conditions,the following recommendations apply based on fracture conductivity behavior relative to proppant particle size:When JRC<46,conductivity increases with larger particle sizes,with 20/40 mesh proppant recommended;When JRC>46,conductivity decreases as particle size increases;40/70 mesh proppant is thus recommended to maintain effective conductivity;At JRC=46,conductivity first increases then decreases with increasing particle size,making 30/50mesh the optimal choice.Theresearch findings provide a theoretical foundation for optimizing fracturing designs and enhancing fracturing performance in the field.展开更多
Garment online shopping has been accepted by more and more consumers in recent years. In online shopping, a buyer only chooses the garment size judged by his own experience without trying-on, so the selected garment m...Garment online shopping has been accepted by more and more consumers in recent years. In online shopping, a buyer only chooses the garment size judged by his own experience without trying-on, so the selected garment may not be the fittest one for the buyer due to the variety of body's figures. Thus, we propose a method of optimal selection of garment sizes for online shopping based on Analytic Hierarchy Process (AHP). The hierarchical structure model for optimal selection of garment sizes is structured and the fittest garment for a buyer is found by calculating the matching degrees between individual's measurements and the corresponding key-part values of ready-to-wear clothing sizes. In order to demonstrate its feasibility, we provide an example of selecting the fittest sizes of men's bottom. The result shows that the proposed method is useful in online clothing sales application.展开更多
In four—dimensional variational data assimilation (4DVAR) technology, how to calculate the optimal step size is always a very important and indeed difficult task. It is directly related to the computational efficienc...In four—dimensional variational data assimilation (4DVAR) technology, how to calculate the optimal step size is always a very important and indeed difficult task. It is directly related to the computational efficiency. In this research, a new method is proposed to calculate the optimal step size more effectively. Both nonlinear one—dimensional advection equation and two—dimensional inertial wave equation are used to test and compare the influence of different methods of the optimal step size calculations on the iteration steps, as well as the simulation results of 4DVAR processes. It is in evidence that the different methods have different influences. The calculating method is very important to determining whether the iteration is convergent or not and whether the convergence rate is large or small. If the calculating method of optimal step size is properly determined as demonstrated in this paper, then it can greatly enlarge the convergence rate and further greatly decrease the iteration steps. This research is meaningful since it not only makes an important improvement on 4DVAR theory, but also has useful practical application in improving the computational efficiency and saving the computational time. Key words 4DVAR - Optimal step size - Iterative convergence rate This work was supported by the National Natural Science Foundation under grants: 49735180 and 49675259, the “973 Project? CHERES(G 1998040907), the Project of Natural Science Foundation of Jiangsu Province(BK99020), and the Project Sponsored by the Scientific Research Foundation for the Returned Overseas Chinese Scholars.展开更多
Energy efficiency is closely related to the evolution of biological systems and is important to their information processing. In this work, we calculate the excitation probability of a simple model of a bistable biolo...Energy efficiency is closely related to the evolution of biological systems and is important to their information processing. In this work, we calculate the excitation probability of a simple model of a bistable biological unit in response to pulsatile inputs, and its spontaneous excitation rate due to noise perturbation. Then we analytically calculate the mutual information, energy cost, and energy efficiency of an array of these bistable units. We find that the optimal number of units could maximize this array＇s energy efficiency in encoding pulse inputs, which depends on the fixed energy cost. We conclude that demand for energy efficiency in biological systems may strongly influence the size of these systems under the pressure of natural selection.展开更多
In developing countries like South Africa,users experienced more than 1030 hours of load shedding outages in just the first half of 2023 due to inadequate power supply from the national grid.Residential homes that can...In developing countries like South Africa,users experienced more than 1030 hours of load shedding outages in just the first half of 2023 due to inadequate power supply from the national grid.Residential homes that cannot afford to take actions to mitigate the challenges of load shedding are severely inconvenienced as they have to reschedule their demand involuntarily.This study presents optimal strategies to guide households in determining suitable scheduling and sizing solutions for solar home systems to mitigate the inconvenience experienced by residents due to load shedding.To start with,we predict the load shedding stages that are used as input for the optimal strategies by using the K-Nearest Neighbour(KNN)algorithm.Based on an accurate forecast of the future load shedding patterns,we formulate the residents’inconvenience and the loss of power supply probability during load shedding as the objective function.When solving the multi-objective optimisation problem,four different strategies to fight against load shedding are identified,namely(1)optimal home appliance scheduling(HAS)under load shedding;(2)optimal HAS supported by solar panels;(3)optimal HAS supported by batteries,and(4)optimal HAS supported by the solar home system with both solar panels and batteries.Among these strategies,appliance scheduling with an optimally sized 9.6 kWh battery and a 2.74 kWp panel array of five 550 Wp panels,eliminates the loss of power supply probability and reduces the inconvenience by 92%when tested under the South African load shedding cases in 2023.展开更多
The efficiency of businesses is often hindered by the challenges encountered in traditional Supply Chain Manage-ment(SCM),which is characterized by elevated risks due to inadequate accountability and transparency.To a...The efficiency of businesses is often hindered by the challenges encountered in traditional Supply Chain Manage-ment(SCM),which is characterized by elevated risks due to inadequate accountability and transparency.To address these challenges and improve operations in green manufacturing,optimization algorithms play a crucial role in supporting decision-making processes.In this study,we propose a solution to the green lot size optimization issue by leveraging bio-inspired algorithms,notably the Stork Optimization Algorithm(SOA).The SOA draws inspiration from the hunting and winter migration strategies employed by storks in nature.The theoretical framework of SOA is elaborated and mathematically modeled through two distinct phases:exploration,based on migration simulation,and exploitation,based on hunting strategy simulation.To tackle the green lot size optimization issue,our methodology involved gathering real-world data,which was then transformed into a simplified function with multiple constraints aimed at optimizing total costs and minimizing CO_(2) emissions.This function served as input for the SOA model.Subsequently,the SOA model was applied to identify the optimal lot size that strikes a balance between cost-effectiveness and sustainability.Through extensive experimentation,we compared the performance of SOA with twelve established metaheuristic algorithms,consistently demonstrating that SOA outperformed the others.This study’s contribution lies in providing an effective solution to the sustainable lot-size optimization dilemma,thereby reducing environmental impact and enhancing supply chain efficiency.The simulation findings underscore that SOA consistently achieves superior outcomes compared to existing optimization methodologies,making it a promising approach for green manufacturing and sustainable supply chain management.展开更多
In this paper,given the shortcomings of jellyfish search algorithmwith low search ability in the early stage and easy to fall into local optimal solution,this paper introduces adaptive weight function and elite strate...In this paper,given the shortcomings of jellyfish search algorithmwith low search ability in the early stage and easy to fall into local optimal solution,this paper introduces adaptive weight function and elite strategy,improving the global search scope in the early stage and the ability to refine the local development in the later stage.In the numerical study,the benchmark problem of dimensional optimization with a 10-bar truss structure and simultaneous dimensional shape optimization with a 15-bar truss structure is adopted,and the corresponding penalty method is used for constraint treatment.The test results show that the improved jellyfish search algorithm can provide better truss sections as well as weights.Because when the steel main truss of the large-span covered bridge is lifted,the site is limited and the large lifting equipment cannot enter the site,and the original structure does not meet the problem of stress concentration and large deformation of the bolt group,so the spreader is used to lift,and the improved jellyfish search algorithm is introduced into the design optimization of the spreader.The results show that the improved jellyfish algorithm can efficiently and accurately find out the optimal shape and weight of the spreader,and throughMidas Civil simulation,the spreader used canmeet the requirements of weight and safety.展开更多
A light?weight design method of integrated structural topology and size co?optimization for the force?performance?structure of complex structural parts is presented in this paper. Firstly, the supporting function of a...A light?weight design method of integrated structural topology and size co?optimization for the force?performance?structure of complex structural parts is presented in this paper. Firstly, the supporting function of a complex structural part is built to map the force transmission, where the force exerted areas and constraints are considered as connecting structure and the structural configuration, to determine the part performance as well as the force routines. Then the connecting structure design model, aiming to optimize the static and dynamic performances on connection configuration, is developed, and the optimum design of the characteristic parameters is carried out by means of the collaborative optimization method, namely, the integrated structural topology optimization and size optimization. In this design model, the objective is to maximize the connecting stiffness. Based on the relationship between the force and the structural configuration of a part, the optimal force transmission routine that can meet the performance requirements is obtained using the structural topology optimization technology. Accordingly, the light?weight design of conceptual configuration for complex parts under multi?objective and multi?condition can be realized. Finally, based on the proposed collaborative optimization design method, the optimal performance and optimal structure of the complex parts with light weight are realized, and the reasonable structural unit configuration and size charac?teristic parameters are obtained. A bed structure of gantry?type machining center is designed by using the proposed light?weight structure design method in this paper, as an illustrative example. The bed after the design optimization is lighter 8% than original one, and the rail deformation is reduced by 5%. Moreover, the lightweight design of the bed is achieved with enhanced performance to show the effectiveness of the proposed method.展开更多
More and more attention has been paid to the high penetration of renewable energy in recent years.The randomness and intermittency of solar and wind energy make it an inevitable trend that renewables are coupled with ...More and more attention has been paid to the high penetration of renewable energy in recent years.The randomness and intermittency of solar and wind energy make it an inevitable trend that renewables are coupled with energy storage technologies.Pumped hydro storage(PHS)is the most widelyused storage form in the power grid but the capacity is limited by geographic conditions.The concentrated solar power(CSP)plant with a thermal energy storage(TES)system can realize easier grid connections and effective peak shaving.Therefore,this paper proposes a solar-wind-hydro hybrid power system with PHS-TES double energy storages,and investigates the optimal coordinated operational strategy and multi-objective sizing.The optimal sizing problem which considers the minimum levelized cost of energy(LCOE)and loss of power supply probability(LPSP)as objectives is solved by multi-objective particle swarm optimization.Moreover,the seasonal uncertainties of renewables are considered by applying a scenario-based analysis using Kmeans clustering.Finally,a case study reveals the effectiveness of the coordinated operational strategy and double energy storages from the perspectives of economy and reliability.The comparisons of optimal sizing results show that the PV-WindCSP-PHS system decreases the LCOE by 19.1%compared to a PV-Wind-CSP system under the same LPSP,and reduces the LPSP compared to PV-Wind-PHS systems with limited reservoir capacity,which indicates that the proposed system with double energy storages has better economy and reliability performance compared to single storage.展开更多
With the development of satellite structure technology, more and more design parameters will affect its structural performance. It is desirable to obtain an optimal structure design with a minimum weight, including op...With the development of satellite structure technology, more and more design parameters will affect its structural performance. It is desirable to obtain an optimal structure design with a minimum weight, including optimal configuration and sizes. The present paper aims to describe an optimization analysis for a satellite structure, including topology optimization and size optimization. Based on the homogenization method, the topology optimization is carried out for the main supporting frame of service module under given constraints and load conditions, and then the sensitivity analysis is made of 15 structural size parameters of the whole satellite and the optimal sizes are obtained. The numerical result shows that the present optimization design method is very effective.展开更多
To obtain bio-inspired structures with superior biological function,four bio-inspired structures named regular arrangement honeycomb structure(RAHS),staggered arrangement honeycomb structure(SAHS),floral arrangement h...To obtain bio-inspired structures with superior biological function,four bio-inspired structures named regular arrangement honeycomb structure(RAHS),staggered arrangement honeycomb structure(SAHS),floral arrangement honeycomb structure(FLAHS)and functional arrangement honeycomb structure(FUAHS)are designed by observing the microstructure of the Gideon beetle,based on the optimal size bio-inspired cells by response surface method(RSM)and particle swarm optimization(PSO)algorithm.According to Euler theory and buckling failure theory,compression deformation properties of bio-inspired structures are explained.Experiments and simulations further verify the accuracy of theoretical analysis results.The results show that energy absorption of FLAHS is,respectively,increased by 26.95%,22.85%,and 121.45%,compared with RAHS,SAHS,and FUAHS.Elastic modulus of FLAHS is 110.37%,110.37%,and 230.56% of RAHS,SAHS,and FUAHS,respectively.FLAHS perfectly inherits crashworthiness and energy absorption properties of the Gideon beetle,and FLAHS has the most stable force.Similarly,RAHS,SAHS,and FUAHS,respectively,inherit mechanical properties of the Gideon beetle top horn,the Gideon beetle middle horn,and the abdomen of the beetle.This method,designing bio-inspired structures with biological functions,can be introduced into the engineering field requiring the special function.展开更多
This study used Ecopath model of the Jiaozhou Bay as an example to evaluate the effect of stomach sample size of three fish species on the projection of this model. The derived ecosystem indices were classified into t...This study used Ecopath model of the Jiaozhou Bay as an example to evaluate the effect of stomach sample size of three fish species on the projection of this model. The derived ecosystem indices were classified into three categories:(1) direct indices, like the trophic level of species, influenced by stomach sample size directly;(2)indirect indices, like ecology efficiency(EE) of invertebrates, influenced by the multiple prey-predator relationships;and(3) systemic indices, like total system throughout(TST), describing the status of the whole ecosystem. The influences of different stomach sample sizes on these indices were evaluated. The results suggest that systemic indices of the ecosystem model were robust to stomach sample sizes, whereas specific indices related to species were indicated to be with low accuracy and precision when stomach samples were insufficient.The indices became more uncertain when the stomach sample sizes varied for more species. This study enhances the understanding of how the quality of diet composition data influences ecosystem modeling outputs. The results can also guide the design of stomach content analysis for developing ecosystem models.展开更多
This research proposes the utilization of a geopolymer-based blasting sealing material to improve the profitability of coal sales and reduce the rate of coal fragmentation during blasting in open pit mines.The study f...This research proposes the utilization of a geopolymer-based blasting sealing material to improve the profitability of coal sales and reduce the rate of coal fragmentation during blasting in open pit mines.The study first focused on optimizing the strength of the sealant material and reducing curing time.This was achieved by regulating the slag doping and sodium silicate solution modulus.The findings demonstrated that increasing slag content and improving the material resulted in an early rise in strength while increasing the modulus of the sodium silicate solution extended the curing time.The slag doping level was fixed at 80 g,and the sodium silicate solution modulus was set at 1.5.To achieve a strength of 3.12 MPa,the water/gel ratio was set at 0.5.The initial setting time was determined to be 33 min,meeting the required field test duration.Secondly,the strength requirements for field implementation were assessed by simulating the action time and force destruction process of the sealing material during blasting using ANSYS/LS-DYNA software.The results indicated that the modified material meets these requirements.Finally,the Shengli Open Pit Coal Mine served as the site for the field test.It was observed that the hole-sealing material’s hydration reaction created a laminated and flocculated gel inside it.This enhanced the density of the modified material.Additionally,the pregelatinized starch,functioning as an organic binder,filled the gaps between the gels,enhancing the cohesion and bonding coefficient of the material.Upon analyzing the post-blasting shooting effect diagram using the Split-Desktop software,it was determined that the utilization of the modified blast hole plugging material resulted in a decrease in the rate of coal fragmentation from 33.2%to 21.1%.This reduction exhibited a minimal error of 1.63%when compared to the field measurement,thereby providing further confirmation of the exceptional plugging capabilities of the modified material.This study significantly contributes to establishing a solid theoretical basis for enhancing the blasting efficiency of open pit mines and,in turn,enhancing their economic advantages.展开更多
This research develops a comprehensive method to solve a combinatorial problem consisting of distribution system reconfiguration, capacitor allocation, and renewable energy resources sizing and siting simultaneously a...This research develops a comprehensive method to solve a combinatorial problem consisting of distribution system reconfiguration, capacitor allocation, and renewable energy resources sizing and siting simultaneously and to improve power system's accountability and system performance parameters. Due to finding solution which is closer to realistic characteristics, load forecasting, market price errors and the uncertainties related to the variable output power of wind based DG units are put in consideration. This work employs NSGA-II accompanied by the fuzzy set theory to solve the aforementioned multi-objective problem. The proposed scheme finally leads to a solution with a minimum voltage deviation, a maximum voltage stability, lower amount of pollutant and lower cost. The cost includes the installation costs of new equipment, reconfiguration costs, power loss cost, reliability cost, cost of energy purchased from power market, upgrade costs of lines and operation and maintenance costs of DGs. Therefore, the proposed methodology improves power quality, reliability and security in lower costs besides its preserve, with the operational indices of power distribution networks in acceptable level. To validate the proposed methodology's usefulness, it was applied on the IEEE 33-bus distribution system then the outcomes were compared with initial configuration.展开更多
文摘The growing global energy demand and the need to mitigate greenhouse gas emissions have driven the explo-ration of sustainable and efficient energy solutions.In Algeria,where the energy sector relies heavily on fossil fuels,integrating renewable energy systems is essential for enhancing energy security and reducing environ-mental impacts.This study focuses on optimizing a hybrid renewable energy system(HRES)for off-grid appli-cations in the Hassi Messaoud region of Algeria to balance technical performance,economic viability,and environmental sustainability.A hybrid system consisting of photovoltaic(PV)panels,wind turbines(WTs),fuel cells(FCs),and diesel generators(DGs)was modeled and optimized using a genetic algorithm(GA).The opti-mization process aims to minimize the annual cost of the system while ensuring high reliability,as measured by the loss of power supply probability,and maximizing the use of renewable energy.A particle swarm optimization(PSO)approach was also implemented for comparison,highlighting the advantages of the GA in terms of cost distribution and system reliability.The optimized HRES demonstrated that renewable sources(PV and WT)provided 77%of the total energy demand,with an overall system cost of 0.18080$⋅kWh^(-1),significantly lower than recent studies,which reported costs between 0.213 and 0.609$⋅kWh^(-1).FCs contributed 14%to the load,whereas DGs were limited to 8%to minimize emissions,resulting in annual CO_(2) emissions of 10,865 kg and a relative emission rate of 3.608 gCO_(2)eq⋅kWh^(-1).Economic analysis showed that DGs and FCs accounted for 44%and 24%of the annual cost,respectively,highlighting the impact of backup systems in ensuring reliability.Sensitivity analysis under varying load demands and renewable energy availability confirmed the robustness of the system,and the GA approach was found to be more effective than PSO in maintaining cost efficiency and reliability.Additionally,the social analysis highlighted a renewable fraction of 91.5%,emphasizing the contribution of the system to sustainable energy practices.These findings validate GA-based optimization as a superior method for designing cost-effective,reliable,and environmentally sustainable HRES,offering significant potential to reduce fossil fuel dependency in industrial applications.These results not only support the broader adoption of renewable energy systems in similar regions but also contribute valuable insights for future research and policy development in the field of energy sustainability.
基金supported by the National Grid ESO Project‘Tool for Co-Optimisation of Energy and Frequency-Containment Services(COEF)’.
文摘Large renewable penetration has been witnessed in power systems, resulting in reduced level of system inertia and increasing requirements for frequency response services. There have been plenty of studies developing frequency-constrained operation models for power system security. However, most existing literature only focuses on operational level rather than planning level. To fill this gap, this paper proposes a novel planning model for the optimal sizing problem of integrated power and gas systems, capturing both under and over frequency security requirements. A detailed unit commitment setup considering different ramping rates is incorporated into the planning model to accurately represent the scheduling behavior of each individual generator and accurate inertia calculation. The power importing and exporting behaviors of interconnectors are considered, which can influence the largest loss of generation and demand, accounting for under and over frequency security, respectively. Additionally, a deep learning-based clustering method featured by concurrent and integrated learning is introduced in the planning model to effectively generate representative days. Case studies have been conducted on a coupled 6-bus power and 7-node gas system as well as a 14-bus power and 14-node gas system to verify the effectiveness of the proposed planning model in accurate clustering performance and realistic investment decision making.
文摘Power loss and voltage uncertainty are the major issues prevalently faced in the design of distribution systems.But such issues can be resolved through effective usage of networking reconfiguration that has a combination of Distributed Generation(DG)units from distribution networks.In this point of view,optimal placement and sizing of DGs are effective ways to boost the performance of power systems.The optimum allocation of DGs resolves various problems namely,power loss,voltage profile improvement,enhanced reliability,system stability,and performance.Several research works have been conducted to address the distribution system problems in terms of power loss,energy loss,voltage profile,and voltage stability depending upon optimal DG distribution.With this motivation,the current study designs a Chaotic Artificial Flora Optimization based on Optimal Placement and Sizing of DGs(CAFO-OPSDG)to enhance the voltage profiles and mitigate the power loss.Besides,the CAFO algorithm is derived from the incorporation of chaos theory concept into conventional artificial flora optimization AFO algorithm with an aim to enhance the global optimization abilities.The fitness function of CAFO-OPSDG algorithm involves voltage regulation,power loss minimization,and penalty cost.To consider the actual power system scenario,the penalty factor acts as an important element not only to minimize the total power loss but to increase the voltage profiles as well.The experimental validation of the CAFO-OPSDG algorithm was conducted against IEEE 33 Bus system and IEEE 69 Bus system.The outcomes were examined under various test scenarios.The results of the experiment established that the presented CAFO-OPSDG model is effective in terms of reducing the power loss and voltage deviation and boost-up the voltage profile for the specified system.
文摘An effective optimization method for the shape/sizing design of composite wing structures is presented with satisfying weight-cutting results. After decoupling, a kind of two-layer cycled optimization strategy suitable for these integrated shape/sizing optimization is obtained. The uniform design method is used to provide sample points, and approximation models for shape design variables. And the results of sizing optimization are construct- ed with the quadratic response surface method （QRSM）. The complex method based on QRSM is used to opti- mize the shape design variables and the criteria method is adopted to optimize the sizing design variables. Compared with the conventional method, the proposed algorithm is more effective and feasible for solving complex composite optimization problems and has good efficiency in weight cutting.
基金supported by the Fundamental Research Funds of the Chinese Academy of Forestry(CAFYBB2020QB004)the National Natural Science Foundation of China(41971038,32171559,U20A2085,and U21A2005).
文摘The sap flow method is widely used to estimate forest transpiration.However,at the individual tree level it has spatiotemporal variations due to the impacts of environmental conditions and spatial relationships among trees.Therefore,an in-depth understanding of the coupling effects of these factors is important for designing sap flow measurement methods and performing accurate assessments of stand scale transpiration.This study is based on observations of sap flux density(SF_(d))of nine sample trees with different Hegyi’s competition indices(HCIs),soil moisture,and meteorological conditions in a pure plantation of Larix gmelinii var.principis-rupprechtii during the 2021 growing season(May to September).A multifactorial model of sap flow was developed and possible errors in the stand scale sap flow estimates associated with sample sizes were determined using model-based predictions of sap flow.Temporal variations are controlled by vapour pressure deficit(VPD),solar radiation(R),and soil moisture,and these relationships can be described by polynomial or saturated exponential functions.Spatial(individual)differences were influenced by the HCI,as shown by the decaying power function.A simple SF_(d)model at the individual tree level was developed to describe the synergistic influences of VPD,R,soil moisture,and HCI.The coefficient of variations(CV)of the sap flow estimates gradually stabilized when the sample size was>10;at least six sample trees were needed if the CV was within 10%.This study improves understanding of the mechanisms of spatiotemporal variations in sap flow at the individual tree level and provides a new methodology for determining the optimal sample size for sap flow measurements.
基金funded by China NationalOffshore Oil Corporation(CNOOC)14th Five-Year Plan Major Science and Technology Project:Research on Integrated Geological Engineering Technology for Fracturing and Development of Offshore Low-Permeability Reservoirs(Grant NO.KJGG2022-0701).Mao Jiang,Chengyong Peng,JiangshuWu and Xuesong Xing.https://www.cnooc.com.cn.
文摘Fracture conductivity is a key factor to determine the fracturing effect.Optimizing proppant particle size distribution is critical for ensuring efficient proppant placement within fractures.To address challenges associated with the low-permeability reservoirs in the Lufeng Oilfield of the South China Sea—including high heterogeneity,complex lithology,and suboptimal fracturing outcomes—JRC(Joint Roughness Coefficient)was employed to quantitatively characterize the lithological properties of the target formation.A CFD-DEM(Computational Fluid Dynamics-Discrete Element Method)two-way coupling approach was then utilized to construct a fracture channel model that simulates proppant transport dynamics.Theproppant particle size under different lithology was optimized.Theresults show that:(1)In rough fractures,proppant particles exhibit more chaotic migration behavior compared to their movement on smooth surfaces,thereby increasing the risk of fracture plugging;(2)Within the same particle size range,for proppants with mesh sizes of 40/70 or 20/40,fracture conductivity decreases as roughness increases.In contrast,for 30/50 mesh proppants,conductivity initially increases and then decreases with rising roughness;(3)Under identical roughness conditions,the following recommendations apply based on fracture conductivity behavior relative to proppant particle size:When JRC<46,conductivity increases with larger particle sizes,with 20/40 mesh proppant recommended;When JRC>46,conductivity decreases as particle size increases;40/70 mesh proppant is thus recommended to maintain effective conductivity;At JRC=46,conductivity first increases then decreases with increasing particle size,making 30/50mesh the optimal choice.Theresearch findings provide a theoretical foundation for optimizing fracturing designs and enhancing fracturing performance in the field.
基金The Programfor New Century Excellent Talents in University from Ministry of Education of China(No.NCET-04-415)the Cultivation Fund of the Key Scientific and Technical Innovation Project from Ministry of Education of China(No.706024)International Science Cooperation Foundation of Shanghai,China(No.061307041)
文摘Garment online shopping has been accepted by more and more consumers in recent years. In online shopping, a buyer only chooses the garment size judged by his own experience without trying-on, so the selected garment may not be the fittest one for the buyer due to the variety of body's figures. Thus, we propose a method of optimal selection of garment sizes for online shopping based on Analytic Hierarchy Process (AHP). The hierarchical structure model for optimal selection of garment sizes is structured and the fittest garment for a buyer is found by calculating the matching degrees between individual's measurements and the corresponding key-part values of ready-to-wear clothing sizes. In order to demonstrate its feasibility, we provide an example of selecting the fittest sizes of men's bottom. The result shows that the proposed method is useful in online clothing sales application.
文摘In four—dimensional variational data assimilation (4DVAR) technology, how to calculate the optimal step size is always a very important and indeed difficult task. It is directly related to the computational efficiency. In this research, a new method is proposed to calculate the optimal step size more effectively. Both nonlinear one—dimensional advection equation and two—dimensional inertial wave equation are used to test and compare the influence of different methods of the optimal step size calculations on the iteration steps, as well as the simulation results of 4DVAR processes. It is in evidence that the different methods have different influences. The calculating method is very important to determining whether the iteration is convergent or not and whether the convergence rate is large or small. If the calculating method of optimal step size is properly determined as demonstrated in this paper, then it can greatly enlarge the convergence rate and further greatly decrease the iteration steps. This research is meaningful since it not only makes an important improvement on 4DVAR theory, but also has useful practical application in improving the computational efficiency and saving the computational time. Key words 4DVAR - Optimal step size - Iterative convergence rate This work was supported by the National Natural Science Foundation under grants: 49735180 and 49675259, the “973 Project? CHERES(G 1998040907), the Project of Natural Science Foundation of Jiangsu Province(BK99020), and the Project Sponsored by the Scientific Research Foundation for the Returned Overseas Chinese Scholars.
基金Supported by the National Natural Science Foundation of China under Grant Nos 11105062 and 11265014the Fundamental Research Funds for the Central Universities under Grant Nos LZUJBKY-2011-57 and LZUJBKY-2015-119
文摘Energy efficiency is closely related to the evolution of biological systems and is important to their information processing. In this work, we calculate the excitation probability of a simple model of a bistable biological unit in response to pulsatile inputs, and its spontaneous excitation rate due to noise perturbation. Then we analytically calculate the mutual information, energy cost, and energy efficiency of an array of these bistable units. We find that the optimal number of units could maximize this array＇s energy efficiency in encoding pulse inputs, which depends on the fixed energy cost. We conclude that demand for energy efficiency in biological systems may strongly influence the size of these systems under the pressure of natural selection.
基金supported by National Key R&D Program of China(Grant No.2021YFE0199000)National Natural Science Foundation of China(Grant No.62133015)+1 种基金National Research Foundation China/South Africa Research Cooperation Programme with Grant No.148762Royal Academy of Engineering Transforming Systems through Partnership grant scheme with reference No.TSP2021\100016.
文摘In developing countries like South Africa,users experienced more than 1030 hours of load shedding outages in just the first half of 2023 due to inadequate power supply from the national grid.Residential homes that cannot afford to take actions to mitigate the challenges of load shedding are severely inconvenienced as they have to reschedule their demand involuntarily.This study presents optimal strategies to guide households in determining suitable scheduling and sizing solutions for solar home systems to mitigate the inconvenience experienced by residents due to load shedding.To start with,we predict the load shedding stages that are used as input for the optimal strategies by using the K-Nearest Neighbour(KNN)algorithm.Based on an accurate forecast of the future load shedding patterns,we formulate the residents’inconvenience and the loss of power supply probability during load shedding as the objective function.When solving the multi-objective optimisation problem,four different strategies to fight against load shedding are identified,namely(1)optimal home appliance scheduling(HAS)under load shedding;(2)optimal HAS supported by solar panels;(3)optimal HAS supported by batteries,and(4)optimal HAS supported by the solar home system with both solar panels and batteries.Among these strategies,appliance scheduling with an optimally sized 9.6 kWh battery and a 2.74 kWp panel array of five 550 Wp panels,eliminates the loss of power supply probability and reduces the inconvenience by 92%when tested under the South African load shedding cases in 2023.
基金This research is funded by the Science Committee of the Ministry of Science and Higher Education of the Republic of Kazakhstan,Grant No.AP19674517.
文摘The efficiency of businesses is often hindered by the challenges encountered in traditional Supply Chain Manage-ment(SCM),which is characterized by elevated risks due to inadequate accountability and transparency.To address these challenges and improve operations in green manufacturing,optimization algorithms play a crucial role in supporting decision-making processes.In this study,we propose a solution to the green lot size optimization issue by leveraging bio-inspired algorithms,notably the Stork Optimization Algorithm(SOA).The SOA draws inspiration from the hunting and winter migration strategies employed by storks in nature.The theoretical framework of SOA is elaborated and mathematically modeled through two distinct phases:exploration,based on migration simulation,and exploitation,based on hunting strategy simulation.To tackle the green lot size optimization issue,our methodology involved gathering real-world data,which was then transformed into a simplified function with multiple constraints aimed at optimizing total costs and minimizing CO_(2) emissions.This function served as input for the SOA model.Subsequently,the SOA model was applied to identify the optimal lot size that strikes a balance between cost-effectiveness and sustainability.Through extensive experimentation,we compared the performance of SOA with twelve established metaheuristic algorithms,consistently demonstrating that SOA outperformed the others.This study’s contribution lies in providing an effective solution to the sustainable lot-size optimization dilemma,thereby reducing environmental impact and enhancing supply chain efficiency.The simulation findings underscore that SOA consistently achieves superior outcomes compared to existing optimization methodologies,making it a promising approach for green manufacturing and sustainable supply chain management.
基金the National Natural Science Foundation of China(Grant No.51305372)the Open Fund Project of the Transportation Infrastructure Intelligent Management and Maintenance Engineering Technology Center of Xiamen City(Grant No.TCIMI201803)the Project of the 2011 Collaborative Innovation Center of Fujian Province(Grant No.2016BJC019).
文摘In this paper,given the shortcomings of jellyfish search algorithmwith low search ability in the early stage and easy to fall into local optimal solution,this paper introduces adaptive weight function and elite strategy,improving the global search scope in the early stage and the ability to refine the local development in the later stage.In the numerical study,the benchmark problem of dimensional optimization with a 10-bar truss structure and simultaneous dimensional shape optimization with a 15-bar truss structure is adopted,and the corresponding penalty method is used for constraint treatment.The test results show that the improved jellyfish search algorithm can provide better truss sections as well as weights.Because when the steel main truss of the large-span covered bridge is lifted,the site is limited and the large lifting equipment cannot enter the site,and the original structure does not meet the problem of stress concentration and large deformation of the bolt group,so the spreader is used to lift,and the improved jellyfish search algorithm is introduced into the design optimization of the spreader.The results show that the improved jellyfish algorithm can efficiently and accurately find out the optimal shape and weight of the spreader,and throughMidas Civil simulation,the spreader used canmeet the requirements of weight and safety.
基金Supported by National Science and Technology Major Project(Grant No.2015ZX04014021)
文摘A light?weight design method of integrated structural topology and size co?optimization for the force?performance?structure of complex structural parts is presented in this paper. Firstly, the supporting function of a complex structural part is built to map the force transmission, where the force exerted areas and constraints are considered as connecting structure and the structural configuration, to determine the part performance as well as the force routines. Then the connecting structure design model, aiming to optimize the static and dynamic performances on connection configuration, is developed, and the optimum design of the characteristic parameters is carried out by means of the collaborative optimization method, namely, the integrated structural topology optimization and size optimization. In this design model, the objective is to maximize the connecting stiffness. Based on the relationship between the force and the structural configuration of a part, the optimal force transmission routine that can meet the performance requirements is obtained using the structural topology optimization technology. Accordingly, the light?weight design of conceptual configuration for complex parts under multi?objective and multi?condition can be realized. Finally, based on the proposed collaborative optimization design method, the optimal performance and optimal structure of the complex parts with light weight are realized, and the reasonable structural unit configuration and size charac?teristic parameters are obtained. A bed structure of gantry?type machining center is designed by using the proposed light?weight structure design method in this paper, as an illustrative example. The bed after the design optimization is lighter 8% than original one, and the rail deformation is reduced by 5%. Moreover, the lightweight design of the bed is achieved with enhanced performance to show the effectiveness of the proposed method.
基金the National Key Research and Development Program of China 2018YFE0128500the Fundamental Research Funds for the Central Universities of China under Grant B210202069.
文摘More and more attention has been paid to the high penetration of renewable energy in recent years.The randomness and intermittency of solar and wind energy make it an inevitable trend that renewables are coupled with energy storage technologies.Pumped hydro storage(PHS)is the most widelyused storage form in the power grid but the capacity is limited by geographic conditions.The concentrated solar power(CSP)plant with a thermal energy storage(TES)system can realize easier grid connections and effective peak shaving.Therefore,this paper proposes a solar-wind-hydro hybrid power system with PHS-TES double energy storages,and investigates the optimal coordinated operational strategy and multi-objective sizing.The optimal sizing problem which considers the minimum levelized cost of energy(LCOE)and loss of power supply probability(LPSP)as objectives is solved by multi-objective particle swarm optimization.Moreover,the seasonal uncertainties of renewables are considered by applying a scenario-based analysis using Kmeans clustering.Finally,a case study reveals the effectiveness of the coordinated operational strategy and double energy storages from the perspectives of economy and reliability.The comparisons of optimal sizing results show that the PV-WindCSP-PHS system decreases the LCOE by 19.1%compared to a PV-Wind-CSP system under the same LPSP,and reduces the LPSP compared to PV-Wind-PHS systems with limited reservoir capacity,which indicates that the proposed system with double energy storages has better economy and reliability performance compared to single storage.
文摘With the development of satellite structure technology, more and more design parameters will affect its structural performance. It is desirable to obtain an optimal structure design with a minimum weight, including optimal configuration and sizes. The present paper aims to describe an optimization analysis for a satellite structure, including topology optimization and size optimization. Based on the homogenization method, the topology optimization is carried out for the main supporting frame of service module under given constraints and load conditions, and then the sensitivity analysis is made of 15 structural size parameters of the whole satellite and the optimal sizes are obtained. The numerical result shows that the present optimization design method is very effective.
基金funded by the National Key R&D Program of China(No.2018YFB1105100)the National Natural Science Foundation of China(No.51975246)+6 种基金Science and Technology Development Program of Jilin Province(YDZJ202101ZYTS134)the Ascl-zytsxm(202013)the Open Project Program of Key Laboratory for Cross-Scale Micro and Nano Manufacturing,Minstry of Education,Changchun University of Science and Technology(CMNM-KF202109)the Program for JLU Science and Technology Innovative Research Team(No.2019TD-34)Jilin Scientific and Technological Development Program(20200404204YY)Interdisciplinary Research Fund for Doctoral Postgraduates of Jilin University(No.101832020DJX052)Interdisciplinary Cultivation Project for Young Teachers and Students(No.415010300078).
文摘To obtain bio-inspired structures with superior biological function,four bio-inspired structures named regular arrangement honeycomb structure(RAHS),staggered arrangement honeycomb structure(SAHS),floral arrangement honeycomb structure(FLAHS)and functional arrangement honeycomb structure(FUAHS)are designed by observing the microstructure of the Gideon beetle,based on the optimal size bio-inspired cells by response surface method(RSM)and particle swarm optimization(PSO)algorithm.According to Euler theory and buckling failure theory,compression deformation properties of bio-inspired structures are explained.Experiments and simulations further verify the accuracy of theoretical analysis results.The results show that energy absorption of FLAHS is,respectively,increased by 26.95%,22.85%,and 121.45%,compared with RAHS,SAHS,and FUAHS.Elastic modulus of FLAHS is 110.37%,110.37%,and 230.56% of RAHS,SAHS,and FUAHS,respectively.FLAHS perfectly inherits crashworthiness and energy absorption properties of the Gideon beetle,and FLAHS has the most stable force.Similarly,RAHS,SAHS,and FUAHS,respectively,inherit mechanical properties of the Gideon beetle top horn,the Gideon beetle middle horn,and the abdomen of the beetle.This method,designing bio-inspired structures with biological functions,can be introduced into the engineering field requiring the special function.
基金The National Natural Science Foundation of China under contract No.31772852the Fundamental Research Funds for the Central Universities under contract No.201612004。
文摘This study used Ecopath model of the Jiaozhou Bay as an example to evaluate the effect of stomach sample size of three fish species on the projection of this model. The derived ecosystem indices were classified into three categories:(1) direct indices, like the trophic level of species, influenced by stomach sample size directly;(2)indirect indices, like ecology efficiency(EE) of invertebrates, influenced by the multiple prey-predator relationships;and(3) systemic indices, like total system throughout(TST), describing the status of the whole ecosystem. The influences of different stomach sample sizes on these indices were evaluated. The results suggest that systemic indices of the ecosystem model were robust to stomach sample sizes, whereas specific indices related to species were indicated to be with low accuracy and precision when stomach samples were insufficient.The indices became more uncertain when the stomach sample sizes varied for more species. This study enhances the understanding of how the quality of diet composition data influences ecosystem modeling outputs. The results can also guide the design of stomach content analysis for developing ecosystem models.
基金financially supported by the National Natural Science Foundation of China (No. 52174131)
文摘This research proposes the utilization of a geopolymer-based blasting sealing material to improve the profitability of coal sales and reduce the rate of coal fragmentation during blasting in open pit mines.The study first focused on optimizing the strength of the sealant material and reducing curing time.This was achieved by regulating the slag doping and sodium silicate solution modulus.The findings demonstrated that increasing slag content and improving the material resulted in an early rise in strength while increasing the modulus of the sodium silicate solution extended the curing time.The slag doping level was fixed at 80 g,and the sodium silicate solution modulus was set at 1.5.To achieve a strength of 3.12 MPa,the water/gel ratio was set at 0.5.The initial setting time was determined to be 33 min,meeting the required field test duration.Secondly,the strength requirements for field implementation were assessed by simulating the action time and force destruction process of the sealing material during blasting using ANSYS/LS-DYNA software.The results indicated that the modified material meets these requirements.Finally,the Shengli Open Pit Coal Mine served as the site for the field test.It was observed that the hole-sealing material’s hydration reaction created a laminated and flocculated gel inside it.This enhanced the density of the modified material.Additionally,the pregelatinized starch,functioning as an organic binder,filled the gaps between the gels,enhancing the cohesion and bonding coefficient of the material.Upon analyzing the post-blasting shooting effect diagram using the Split-Desktop software,it was determined that the utilization of the modified blast hole plugging material resulted in a decrease in the rate of coal fragmentation from 33.2%to 21.1%.This reduction exhibited a minimal error of 1.63%when compared to the field measurement,thereby providing further confirmation of the exceptional plugging capabilities of the modified material.This study significantly contributes to establishing a solid theoretical basis for enhancing the blasting efficiency of open pit mines and,in turn,enhancing their economic advantages.
文摘This research develops a comprehensive method to solve a combinatorial problem consisting of distribution system reconfiguration, capacitor allocation, and renewable energy resources sizing and siting simultaneously and to improve power system's accountability and system performance parameters. Due to finding solution which is closer to realistic characteristics, load forecasting, market price errors and the uncertainties related to the variable output power of wind based DG units are put in consideration. This work employs NSGA-II accompanied by the fuzzy set theory to solve the aforementioned multi-objective problem. The proposed scheme finally leads to a solution with a minimum voltage deviation, a maximum voltage stability, lower amount of pollutant and lower cost. The cost includes the installation costs of new equipment, reconfiguration costs, power loss cost, reliability cost, cost of energy purchased from power market, upgrade costs of lines and operation and maintenance costs of DGs. Therefore, the proposed methodology improves power quality, reliability and security in lower costs besides its preserve, with the operational indices of power distribution networks in acceptable level. To validate the proposed methodology's usefulness, it was applied on the IEEE 33-bus distribution system then the outcomes were compared with initial configuration.
